Fatores-chave de sucesso na adoção de aplicativos móveis de táxi

A pesquisa tem como objetivo investigar os fatores-chave de sucesso na adoção de aplicativos móveis de táxi (AMTs) por taxistas. Baseando-se nos modelos de Aceitação Tecnológica (DAVIS; BAGOZZI; WARSHAW, 1989), Difusão da Inovação (ROGERS, 1995) e de Confiança (CARTER; BÉLANGER, 2005), o trabalho propõe também uma revisão da literatura de Aplicações Móveis aplicada ao contexto dos AMTs (VAN BILJON; KOTZÉ, 2007). Para o propósito dessa pesquisa, os AMTs são definidos como aplicativos de serviço móvel avançado que viabilizam, por meio de Internet e geolocalização, a solicitação de transporte de táxi em dispositivos móveis, mediante sistemas de informação e chamadas telefônicas, e o acompanhamento da prestação do serviço e seu pagamento. A partir de entrevistas semiestruturadas em profundidade e aplicações de questionários em pesquisa de campo, o estudo propõe uma triangulação de métodos de Análise Lexical (BOTTA,2010; GEERAERTS,2010), Conteúdo (BARDIN,2006) e Ranking Médio (OLIVEIRA,2005) para a investigação dos fatores identificados na literatura. Os resultados apontam que os fatores influenciadores do sucesso dos AMTs, na perspectiva de uso pelos motoristas de táxi, são Simplicidade e Utilidade Percebida, enquanto os moderadores são Segurança e Ganhos Financeiros. Acredita-se que a pesquisa poderá contribuir para a discussão de um tema ainda pouco explorado na literatura no Brasil, os Aplicativos Móveis, além de proporcionar implicações gerenciais no âmbito da inovação em empresas desenvolvedoras.

Testing unit root based on partially adaptive estimation

This paper proposes unit tests based on partially adaptive estimation. The proposed tests provide an intermediate class of inference procedures that are more efficient than the traditional OLS-based methods and simpler than unit root tests based on fully adptive estimation using nonparametric methods. The limiting distribution of the proposed test is a combination of standard normal and the traditional Dickey-Fuller (DF) distribution, including the traditional ADF test as a special case when using Gaussian density. Taking into a account the well documented characteristic of heavy-tail behavior in economic and financial data, we consider unit root tests coupled with a class of partially adaptive M-estimators based on the student-t distributions, wich includes te normal distribution as a limiting case. Monte Carlo Experiments indicate that, in the presence of heavy tail distributions or innovations that are contaminated by outliers, the proposed test is more powerful than the traditional ADF test. We apply the proposed test to several macroeconomic time series that have heavy-tailed distributions. The unit root hypothesis is rejected in U.S. real GNP, supporting the literature of transitory shocks in output. However, evidence against unit roots is not found in real exchange rate and nominal interest rate even haevy-tail is taken into a account.

A Common-feature approach for testing present-value restrictions with financial data

It is well known that cointegration between the level of two variables (labeled Yt and yt in this paper) is a necessary condition to assess the empirical validity of a present-value model (PV and PVM, respectively, hereafter) linking them. The work on cointegration has been so prevalent that it is often overlooked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. The basis of this result is the use of rational expectations in forecasting future values of variables in the PVM. If this condition fails, the present-value equation will not be valid, since it will contain an additional term capturing the (non-zero) conditional expected value of future error terms. Our article has a few novel contributions, but two stand out. First, in testing for PVMs, we advise to split the restrictions implied by PV relationships into orthogonality conditions (or reduced rank restrictions) before additional tests on the value of parameters. We show that PV relationships entail a weak-form common feature relationship as in Hecq, Palm, and Urbain (2006) and in Athanasopoulos, Guillén, Issler and Vahid (2011) and also a polynomial serial-correlation common feature relationship as in Cubadda and Hecq (2001), which represent restrictions on dynamic models which allow several tests for the existence of PV relationships to be used. Because these relationships occur mostly with nancial data, we propose tests based on generalized method of moment (GMM) estimates, where it is straightforward to propose robust tests in the presence of heteroskedasticity. We also propose a robust Wald test developed to investigate the presence of reduced rank models. Their performance is evaluated in a Monte-Carlo exercise. Second, in the context of asset pricing, we propose applying a permanent-transitory (PT) decomposition based on Beveridge and Nelson (1981), which focus on extracting the long-run component of asset prices, a key concept in modern nancial theory as discussed in Alvarez and Jermann (2005), Hansen and Scheinkman (2009), and Nieuwerburgh, Lustig, Verdelhan (2010). Here again we can exploit the results developed in the common cycle literature to easily extract permament and transitory components under both long and also short-run restrictions. The techniques discussed herein are applied to long span annual data on long- and short-term interest rates and on price and dividend for the U.S. economy. In both applications we do not reject the existence of a common cyclical feature vector linking these two series. Extracting the long-run component shows the usefulness of our approach and highlights the presence of asset-pricing bubbles.

A irracionalidade na tomada de decisão: uma abordagem sobre os efeitos chamariz e âncora

Diversos modelos e teorias econômicas neoclássicas se baseiam nos princípios de racionalidade dos indivíduos. No entanto, muitos estudos vêm mostrando como tais princípios podem ser falhos em diversos contextos. Esta pesquisa buscou contribuir com tal literatura através do desenvolvimento de um experimento realizado com alunos de graduação no qual foram testadas aplicações dos vieses de racionalidade conhecidos como Efeito Chamariz e Efeito Âncora. Foram analisados 142 questionários que aparentemente visavam traçar o perfil dos estudantes através de perguntas sobre suas preferências quanto a oportunidades de emprego considerando múltiplos aspectos (remuneração, estabilidade, carga horária e chances de crescimento profissional). Ao longo das questões, no entanto, foram inseridas âncoras e chamarizes. Como resultados, observamos que, ao procurar um emprego, a maioria dos estudantes valoriza principalmente as chances de crescimento profissional e a remuneração oferecida pelo trabalho, ao passo que a carga horária é o atributo de menor peso em suas decisões. Embora o restante de suas respostas fosse bastante coerente com o perfil traçado, os vieses de racionalidade se mostraram influentes. Os chamarizes usados levaram a alterações nas respostas de 7 a 8%, enquanto que o uso de âncoras se mostraram capazes de influenciar o valor mínimo pelo qual os respondentes aceitariam prestar um serviço, violando os princípios de racionalidade.

Simulation-based smoothing and filtering in factor stochastic volatility models : two econometric applications

In this article we use factor models to describe a certain class of covariance structure for financiaI time series models. More specifical1y, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. We build on previous work by allowing the factor loadings, in the factor mo deI structure, to have a time-varying structure and to capture changes in asset weights over time motivated by applications with multi pIe time series of daily exchange rates. We explore and discuss potential extensions to the models exposed here in the prediction area. This discussion leads to open issues on real time implementation and natural model comparisons.

Simulation -based smoothing and filtering in factor stochastic volatility models : two econometric applications (July-2001)

The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.